Fake News in the Business World: the Main Types and the Implications of the 2016 U.S

Fake News in the Business World: The Main Types and the Implications of the 2016 U.S. Presidential Election

Xiaomeng Lan, Ph.D. Beijing Normal University-Hong Kong Baptist University United International College [email protected]

Leping You, Ph.D. Miami University

Abstract

This study aims to improve the understanding of modern fake news as it concerns companies. Specifically, the study attempts to identify the main features of the companies targeted by fake news, the thematic issues of fake news, the stakeholders mentioned or implicated, and the different types of fake news. Considering the 2016 United States presidential election was a dominant theme in the societal discourse when the concept of fake news was popularized, this study also investigated the potentially differing dynamics of fake news about companies across three different time frames—before, during, and after the election process. A qualitative content analysis of 61 business-related fake news claims was conducted. They have been fact-checked and found to contain at least significant false elements—they were rated by the fact-checking website Snopes as “false” (n = 27), “mostly false” (n = 13), or “mixture” (n = 21). The sample data covered the 2016 U.S. presidential election cycle (February 1, 2016–January 20, 2017), as well as the year prior to and the year after this period (i.e., February 1, 2015–January 31, 2016, and January 21, 2017–January 21, 2018, respectively). Results indicated that large, publicly traded companies based in the US were more likely to become the target of fake news. The majority of the fake news stories were related to products and services, and consumers and customers were the major stakeholders. Many other fake news claims were about corporate political involvement or race relations, and thus took on a political tone or character. However, the 2016 U.S. presidential election seemed not to have much influence on the content of the fake news stories. Furthermore, misleading content, false connection, and fabricated content were the most common types of fake news about companies. This study presents one of the first examinations of fake news in the business world. As companies have long been a target of deliberate misinformation and hoaxes, an empirical examination of different aspects and components of fake news as well as the linkages between fake news and sociopolitical contexts would fill important gaps in the existing research on fake news.

Keywords: Fake news, disinformation, misinformation

The publication and dissemination of false stories is hardly new, but the term “fake news” has seen an “unprecedented” rise in use since 2016 and consequently acquired a certain paradoxical legitimacy after being named “Word of the Year 2017” by Collins Dictionary (“Fake news,” 2017). From being merely a description of a social media phenomenon to a perceived threat to democracy and public order, fake news has become a politically and ideologically charged issue (Titcomb & Carson, 2018). This has been fueled largely by the prevalent and quickly spreading spurious election news stories on social media during the 2016 United States presidential election campaign, as well as by U.S. president Donald Trump, who frequently uses the term to discredit unfavorable journalistic scrutiny of his campaign and presidency (Brummette, DiStaso, Vafeiadis, & Messner, 2018; Silverman, 2016; Wendling, 2018). Scholars and media elites have connected the popularization of the term to a number of factors. These include the rise of social media as a main source of news and information (Allcott & Gentzkow, 2017; Berthon & Pitt, 2018), ideological polarization and directionally motivated selective exposure among Internet news users (Narayanan et al., 2018; Spohr, 2017), economic incentives for producing misinformation for online advertising markets and popular social networks such as Facebook (Berthon & Pitt, 2018; Silverman & Alexander, 2016; Wendling, 2018), as well as the undermining of society’s trust in traditional journalism’s ability to ensure accuracy and fairness in news reporting (Allcott & Gentzkow, 2017; Erlanger, 2017; Titcomb & Carson, 2018). As a result, some have argued that we now find ourselves in a “post-truth” world, in which objective facts are overshadowed by appeals to emotions and personal beliefs (Berthon & Pitt, 2018). While much recent academic research has been devoted to fake news in sociopolitical contexts as well as its effects on viewers’ political attitudes and behaviors (e.g., Allcott & Gentzkow, 2017; Guess, Nyhan, & Reifler, 2018; Spohr, 2017), far less attention has been paid to its implications for businesses, with a few exceptions (Berthon & Pitt, 2018; Chen & Cheng, 2019; Ewing & Lambert, 2019; Mills & Robson, 2019; Visentin, Pizzi, & Pichierri, 2019). In fact, companies were already targets of disinformation and hoaxes, though political elections affected the nature of these attacks in some cases. For example, PepsiCo fell victim to fakery in November 2016 when a number of websites quoted CEO Indra Nooyi as allegedly stating that supporters of Donald Trump should “take their business elsewhere” (Picchi, 2016). In August 2017, images purporting to advertise “Starbucks Dreamer Day” claimed that the coffee chain planned to give a deep discount to undocumented American immigrants as a gesture of support (Kuchler, 2017). Furthermore, while large companies have long been targeted by false stories, fake news sites have recently emerged on the Internet that create artificial news articles about small businesses (Reisinger, 2017). Disturbingly, studies have suggested that many people who see fake news stories actually believe them, even if the stories do not fit their ideological bias (Silverman & Singer-Vine, 2016). The various flavors of fake news today present a potent threat to the business community. In fact, fake news as a looming issue for companies is receiving increased attention from public relations practitioners, who have pointed to the need for a crisis communication plan that includes fake news scenarios (Agudelo, 2017; Dietrich, 2018; Gordon, 2018; Guillory, 2018; Liffreing, 2016). However, the influence of fake news on businesses, as well as its implications for the theorization and practical application of current issues management and crisis management models, constitutes an underexplored area of public relations research. This study is an initial effort to fill this research gap by improving the understanding of modern fake news as it concerns companies. Specifically, since the 2016 U.S. presidential election was a dominant

3 Public Relations Journal Vol. 13 Issue 4 (October 2020) © 2020 Institute for Public Relations theme in the societal discourse at the time the concept of fake news was popularized (Allcott & Gentzkow, 2017; Heiskanen & Butters, 2017), this study investigates the potentially differing dynamics of fake news about companies across three different time frames—before, during, and after the 2016 U.S. presidential election process.

Literature Review

History and Conceptualization of “Fake News” The surge in use of the phrase “fake news” coincided with the 2016 U.S. presidential election. Data from Google Trends indicate that “fake news” was rarely used before November 2016, the month of the election (Fallon, 2017). Collins Dictionary (“Fake news,” 2017) said that usage of the word had increased by 365% since 2016, and provided this definition: “false, often sensational, information disseminated under the guise of news reporting.” Many studies have pointed to the sheer scale of false content being disseminated on social networks and posted to fake news sites during that time, and to their feared impact on elections. For example, a study by the Knight Foundation (Hindman & Barash, 2018) found that more than 6.6 million tweets circulated across Twitter linking to fake and conspiracy news publishers in the month before the 2016 election. A BuzzFeed News analysis (Silverman, 2016) found that during the election, false election reports inspired more engagement on Facebook than those from mainstream media sources. A study from Stanford University (Allcott & Gentzkow, 2017) revealed that fake news websites received 159 million visits during the month of the election. Some blamed organized efforts and systematic misinformation campaigns for the spread of falsehoods, which was amplified by social media platforms and automated technology (Berger, 2018; Titcomb & Carson, 2018). Despite the concurrence of the word’s emergence and the 2016 U.S. election, “fake news” is today much more than a label for political false information that is disguised and disseminated as news on social media (Ireton & Posetti, 2018). A variety of things—such as misinformation, disinformation, spin, conspiracy theories, propaganda, mistakes, sloppy or biased reporting by news organizations, and news stories that people just do not like—have all been rolled into the term (Edelman, 2017; Wendling, 2018). The phrase is vulnerable to being politicized and deployed as a weapon to challenge fact and opinion that does not fit into one’s own ideology (Brummette et al., 2018). There is President Trump, for example, who constantly refers to articles published by outlets such as CNN and The New York Times as “fake news” (Titcomb & Carson, 2018). This is not limited to the US, however; as Harvard’s Claire Wardle pointed out, the term “is being used globally by politicians to describe information that they don’t like, and increasingly, that’s working” (Giuliani-Hoffman, 2017). Similarly, publications that are blatantly supportive of one political viewpoint or party and highly partisan news sites such as Breitbart are often referred to as fake news (Titcomb & Carson, 2018). The ubiquity of the term has created epistemological discussions in academia about how fake news should be conceptualized and studied. Focusing on the election-related news stories that were categorized as false by leading fact-checking websites, Allcott and Gentzkow (2017) defined fake news in a narrow sense as “news articles that are intentionally and verifiably false, and could mislead readers” (p. 213). The researchers distinguished the term from related concepts such as unintentional reporting mistakes, rumors that did not originate from media sources, satire not meant to be construed as factual, false statements by politicians, reports that

4 Public Relations Journal Vol. 13 Issue 4 (October 2020) © 2020 Institute for Public Relations were biased or misleading rather than false, as well as conspiracy theories that were efforts “to explain some event or practice by reference to the machinations of powerful people, who attempt to conceal their role” (Sunstein & Vermeule, 2009, p. 205). Unlike Allcott and Gentzkow (2017), Tandoc Jr., Lim, and Ling (2018) viewed fake news as a more comprehensive concept. They identified six types of fake news described in the research literature published between 2003 and 2017: news satire, news parody, fabrication, manipulation, advertising, and propaganda. According to this categorization, news satire in The Daily Show with Jon Stewart and The Colbert Report is also a type of fake news, as the news format is fake—even though it is based on actual events. Similarly, Brummette et al. (2018) considered such satirical and comedic news shows a form of fake news, together with online publications that are intentionally or knowingly false. Lazer and his colleagues (Lazer et al., 2018) defined fake news as “fabricated information that mimics news media content in form but not in organizational process or intent” (p. 1094). In this definition, fake news outlets are those that have the trappings of legitimately produced news but “lack the news media’s editorial norms and processes for ensuring the accuracy and credibility of information” (p. 1094). The attribution of “fakeness” is thus not only at the level of the story but also at that of the publisher. Acknowledging the conceptual overlaps of fake news with other notions such as misinformation and disinformation, the researchers nonetheless endorsed the value of this term as a scientific construct, given its political and societal salience that has drawn attention to an important subject. Kalsnes (2018) concluded that fake news has typically been characterized in terms of format, veracity, and intentionality. She thus defined fake news as “completely or partly false information, (often) appearing as news, and typically expressed as textual, visual or graphical content with an intention to mislead or confuse users” for political or economic purposes (para. 19). Some scholars have shunned the term “fake news” due to its vagueness in usage and its potential for undermining the credibility of journalism; instead, “misinformation” and “disinformation” were the most frequently used alternatives (Giglietto, Iannelli, Rossi, & Valeriani, 2016; Giuliani-Hoffman, 2017; Guess et al., 2018; Marwick & Lewis, 2017; McCorkindale, 2019; Wardle & Derakhshan, 2017). The distinction between misinformation and disinformation does not lie in the veracity of the content—both are false information—but rather in whether the person who is disseminating it knows it is false (Wardle & Derakhshan, 2018). Despite the difference between misinformation and disinformation, much of the discourse on fake news conflates them, referring to the two notions interchangeably (Huberman, 2019; Marwick & Lewis, 2017; Wardle & Derakhshan, 2018). To summarize, even though the term fake news has multiple definitions, there appears to be a broad agreement that it is basically false information purporting to be true. Previous research has relied on fact-checking organizations when operationalizing the concept, and stories verified as false by these third-party sources were studied as fake news (e.g., Allcott & Gentzkow, 2017; Grinberg, Joseph, Friedland, Swire-Thompson, & Lazer, 2019; Vosoughi, Roy, & Aral, 2018). This is arguably the optimal method for delineating the concept, as determining falsity is relatively easier and more reliable than judging the intention of the authors and distributors of the fake news (Verstraete, Bambauer, & Bambauer, 2017). For the purposes of this study, fake news is defined as stories, targeted at companies, that have been fact-checked and found to contain at least significant false elements.

Implications of Fake News for Business An increasing number of scholars are exploring the impact of fake news on businesses. Berthon and Pitt (2018) argued that brands could be impacted directly or indirectly in four fake news scenarios: companies being the target of fake news or appearing in fake news stories, corporate ads appearing by the side of fake news stories, corporate ads appearing on conservative- or liberal-leaning news websites such as Breitbart, and companies being found to finance fake news either directly or indirectly. The authors suggested that brands should try to minimize any association contamination by, for example, reducing the reliance on algorithm- based advertising services. Mills and Robson (2019), too, discussed the threat of fake news from the perspective of brand management. The major argument was that the value of a brand is conversationally co-created by the company and many different stakeholders. The negative impact of fake news on brand value could be offset by strategic use of brand storytelling, which is a powerful tool for persuasion and meaning transfer. Visentin et al. (2019) were among the first to empirically investigate the influences of the fake news phenomenon on brands. The researchers found that there were indirect paths by which fake news could have affected people’s perceptions of a brand whose advertisement appeared adjacent to the false content. Interestingly, the negative effects of this association on people’s attitudes toward the brand and their behavioral intentions took place regardless of the media platforms where the news appeared. The findings suggest that companies should avoid having their advertisements appear near or in conjunction with news that may not be reliable or accurate. Chen and Cheng (2019) empirically examined how fake news messages about brands on Facebook were processed and received by consumers and the possible consequences for brand trust. The study revealed that people’s persuasion knowledge (i.e., people’s personal knowledge about persuasion agents’ goals and tactics; Friestad & Wright, 1994) regarding Facebook played a key role in determining the perceived relevance and usefulness of the problematic content as well as the subsequent brand trust. The more sceptical the consumers were about Facebook’s role as a persuasive tool used by content publishers, the less influence the fake news had on their trust of the brand that appeared in the false content. Still, more research is urgently needed to explore the ramifications of the fake news phenomenon for businesses. The purpose of this study was to undertake a preliminary evaluation of contemporary fake news about companies and to answer the following research questions. RQ1: What have been the main targets of fake news? RQ2: What have been the main thematic issues of fake news? RQ3: Which stakeholders have been involved? RQ4: What influence, if any, did the 2016 U.S. presidential election have on fake news targeting companies? RQ5: What have been the different types of fake news created and shared about companies?

Method

In order to answer these research questions, a qualitative content analysis was conducted. Content analysis has been broadly defined as “any technique for making inferences by objectively and systematically identifying specified characteristics of messages” (Holsti, 1969, p.

14). Under this definition, content analysis is not restricted to textual analysis but may be applied to other forms of content, such as context information (Mayring, 2000; Stemler, 2001). This approach is especially applicable to a relatively new phenomenon about which insufficient or fragmented knowledge has been developed (Hamad, Savundranayagam, Holmes, Kinsella, & Johnson, 2016). Sample Following past approaches to studying fake news (Allcott & Gentzkow, 2017; Grinberg et al., 2019; Vosoughi et al., 2018), this study collected a sample of fake news stories that were characterized as false (either partially or completely) by a leading fact-checking website called Snopes (https://www.snopes.com/). Snopes is one of the fact-checking sites Facebook partners with to clamp down on viral fake news (Mosseri, 2016). Unlike Facebook’s other fact-checker partners, such as PolitiFact, Snopes has documented the spread of business-related fake news and provides examples of the fake news story in circulation as well as detailed information about the main claim (content) of the fake news story, its evolution, its source when known, distribution channels, and the company’s responses (Friggeri, Adamic, Eckles, & Cheng, 2014). The sample for this study was found under the website’s “Archive” tab and “Business” category (https://www.snopes.com/fact-check/category/business/) and was temporally defined by the 2016 U.S. presidential election cycle (from the start of the presidential primaries on February 1, 2016, in Iowa to Inauguration Day on January 20, 2017), as well as the year prior to and the year after this period (i.e., February 1, 2015–January 31, 2016, and January 21, 2017–January 21, 2018, respectively). In total, 135 articles were found. After initial examination of the dataset, 74 articles were excluded from analysis for the following reasons: (a) they were not verified as false (n = 50); (b) they were not about a company but rather a nonprofit organization, a general industrial sector, or unspecified companies (n = 22); or (c) they were incorrectly rated by Snopes (n = 2). Among the 50 articles excluded because falsity was not verified, 22 were rated by Snopes as “true,” 11 “unproven,” five “outdated” (meaning they might have been true in previous contexts), five “mostly true,” three “legend” (meaning they might be exaggerated but not necessarily false), and four left unrated. The remaining 61 articles, rated as “false” (n = 27), “mostly false” (n = 13), or “mixture” (n = 21), were coded and analyzed. Coding Individual Snopes articles served as the unit of analysis and were evaluated by two coders. Following Haney, Russell, Gulek, and Fierros (1998) and Mayring (2014), two coders first independently reviewed about 43% of the dataset (n = 26) and came up with a list of variables and features of fake news. They then met to compare notes and reach agreement on the initial coding items. A formal content analysis followed. A coding sheet was used to record the claim (content) of the fake news story, company name, thematic issues, stakeholders involved, identifiable source of the fake news and media channel(s) through which the fake news was distributed, corporate responses that followed, and politicization (i.e., if the particular fake news item took on a political tone or character; Merriam-Webster, “Politicize,” n.d.). After independent coding of the entire sample, the coders met to discuss their results. Any disagreements between the coders were discussed until a case-by-case consensus was reached. Intercoder reliability was not quantified for these inductive coding items due to the interpretive nature of the analysis process, which used the content itself as a source for generating categories and data.

Following Wardle and Derakhshan’s (2017) categories of misinformation and disinformation, this study examined six types of fake news about companies: false connection, misleading content, false context, imposter content, manipulated content, and fabricated content. The definitions for these types are presented in Table 1. We considered the six types as an exhaustive list, so we assigned each of the sample stories to one of these type categories. Intercoder reliability for this item was assessed using Krippendorff’s alpha (Hayes & Krippendorff, 2007) and the k-alpha coefficient was .74. As recommended by methodologists, k- alpha coefficients of .70 or greater were considered sufficiently reliable for accepting content analysis findings (Lombard, Snyder‐Duch, & Bracken, 2002). The analyses also included three firm-level attribute variables: company size (small– medium businesses—companies with 100–999 employees; medium-sized businesses— companies with 1,000–9,999 employees; or large enterprises—companies that had more than 10,000 employees), industry classification (e.g., hypermarkets and supercenters, restaurants, general merchandise stores, or department stores), and company type (public or private). These data were collected using Standard & Poor’s NetAdvantage database and Hoover’s database.

Results

RQ1 asked whom the main targets of fake news had been. Descriptive statistics showed that, from February 1, 2015, to January 21, 2018, 47 companies became the target of 61 different fake news items. Companies such as Walmart (and its subsidiary Sam’s Club), Target, Wendy’s, Costco, McDonald’s, NIKE, and Mondelez International (which owns the brand Oreo) were targeted more than once. Most of the companies were based in the US (n = 53), while the rest were multinational companies headquartered in the United Kingdom, Australia, Japan, Canada, Italy, and Switzerland. More than half of the companies (57.4%) were publicly listed firms, while 41.0% were privately held. Large enterprises were the most common victims, as they were the protagonists in 68.9% of the stories. In comparison, 13.1% of the stories were about medium- sized companies and 9.8% about small–medium businesses. In terms of the industry type, the businesses in the sample came from a variety of sectors ranging from airlines to leisure products to food retail, but the most affected industries included restaurants (n = 8; e.g., Chick-fil-A and Starbucks), hypermarkets and supercenters (n = 7; e.g., Walmart and Costco), general merchandise stores (n = 5; e.g., Target), packaged foods and meats (n = 5; e.g., Mars and Nestlé), and footwear (n = 3; e.g., NIKE and Vans). The companies and their primary industries are summarized in Table 2. RQ2 asked what the main thematic issues of fake news were. In total, 23 thematic issues were identified in the stories. Most of the stories involved more than one issue, but we only recorded the most salient one, so the thematic issues were mutually exclusive. In fact, a company was often targeted by a complex story that included three or more issues. For example, in a story that claimed Congress had voted to give Apache land to an environmentally exploitative foreign corporation (Snopes, 2017), six issues were identified: corporate environmental practices, race relations, legislation and regulation, foreign investment and local resources, corporate political involvement, and patriotism. For this particular fake news story, foreign investment and local resources was the most salient issue. Among the 23 issues, the most prominent was product conspiracies (n = 8), followed by alleged bad service (n = 7), promotion and freebies (n = 6),

8 Public Relations Journal Vol. 13 Issue 4 (October 2020) © 2020 Institute for Public Relations race relations (n = 6), corporate political involvement (n = 5), and product quality and safety (n = 3). The entire list of thematic issues identified from the fake news stories is given in Table 3. RQ3 asked which stakeholders had been involved. Many different types of company stakeholders were involved in the fake news stories. As with the thematic issues, most stories contained more than one stakeholder. For each sample story, we recorded all the mentioned or implicated stakeholders, so the stakeholders were not mutually exclusive. Of the 15 types of stakeholders identified, customers or consumers were the most commonly mentioned or implicated, as 54.1% of the sample stories (n = 33) contained this stakeholder. This was followed by nonprofit organizations (including activist groups; n = 14), racial and ethnic groups (n = 10), employees (n = 9), foreign countries and foreign leaders (n = 9), governments and government officials (n = 6), slanted websites (n = 5), members of Congress and lawmakers (n = 4), and Donald Trump (n = 3). Table 4 presents the full list of the stakeholders. RQ4 asked what influence, if any, the 2016 U.S. presidential election had on fake news targeting companies. The coders found that 44.3% (n = 27) of the sample was politicized, meaning that these pieces of fake news gave a political tone or character to the stories. Among these politicized stories, 37.0% (n = 10) were circulated during the 2016 U.S. presidential election cycle, compared with 29.6% (n = 8) and 33.3% (n = 9) that were distributed before and after the election campaign, respectively. The differences in the numbers of politicized stories across the three periods were not significant. This suggests that the election did not make much difference in the number of politicized fake news stories about companies. The politicized stories involved various thematic issues, ranging from target of activism to minimum wage, but most frequently they were about race relations (n = 6) and corporate political involvement (n = 5). Other salient issues found in the politicized stories were: employment and hiring practices (n = 2), foreign investment and local resources (n = 2), minimum wage (n = 2), target of activism (n = 2), anti-corporatism (n = 1), historical corporate controversies (n = 1), lawsuit and legal issue (n = 1), patriotism (n = 1), price fluctuation and unwanted fees (n = 1), religious issue (n = 1), and veteran-related issue (n = 1). Nonprofit organizations (including activist groups; n = 10) and racial and ethnic groups (n = 10) were the most mentioned or implicated stakeholders in the politicized fake news stories. They were followed by employees (n = 7), customers or consumers (n = 6), governments and government officials (n = 6), foreign countries and foreign leaders (n = 5), members of Congress and lawmakers (n = 4), slanted websites (n = 4), Donald Trump (n = 3), business leaders (n = 2), political parties (n = 2), protesters (n = 2), and veterans (n = 1). RQ5 asked what different types of fake news about companies had been created and shared. Among the 61 sample fake news stories, 36.1% (n = 22) were characterized by misleading content, 26.2% (n = 16) by false connection, 21.3% (n = 13) by fabricated content, 11.5% (n = 7) by false context, 3.3% (n = 2) by manipulated content, and 1.6% (n = 1) by imposter content. A cross tabulation of the types of fake news stories and politicization indicated that, among the six types of fake news stories, misleading content was the most frequently politicized type of fake news (n = 14), followed by fabricated content (n = 5), false connection (n = 3), false context (n = 3), and manipulated content (n = 2). A cross tabulation of the types of fake news stories and the three time periods (i.e., before, during, and after the 2016 U.S. presidential election cycle) indicated that the number of false connection stories surged (n = 9) during the election cycle, compared to the year prior (n = 4) and the year after this period (n = 3). This relatively large change in the number of stories featuring false connection across the three periods was not seen in other types of fake news. Comparing types of fake news with thematic

9 Public Relations Journal Vol. 13 Issue 4 (October 2020) © 2020 Institute for Public Relations issue types revealed that some types of fake news were more frequently associated with specific issue topics. For example, for misleading content, the most common thematic issue observed was corporate political involvement (n = 3). For fabricated content, the most common issue topics were product conspiracies (n = 4) and race relations (n = 3).

Discussion and Conclusions

The aim of this study was to examine different business-related fake news stories that were created and shared during the period from February 1, 2015, to January 21, 2018, as well as the possible influence of the 2016 U.S. presidential election campaign—which took place within that time frame—on fake news related to the business world. The data indicated that large, publicly traded companies based in the US were more likely to become targets of fake news. The majority of the fake news stories were related to products and services, and consumers and customers were the major stakeholders in those stories. Many other fake news claims were about corporate political involvement or race relations, and thus took on a political tone or character. However, the 2016 U.S. presidential election seemed not to have much influence on the content of the fake news stories, as no significant surge in the number of politicized fake news claims during the election cycle was observed (though this may be because our sample size was too small). Furthermore, we found that misleading content, false connection, and fabricated content were the most common types of fake news about companies, together accounting for more than 80% of the entire sample. Misleading content, defined as “misleading use of information to frame an issue or an individual” (Wardle, 2017), by itself accounted for about one-fourth of the sample stories. Misleading content typically involved at least some facts, although the facts were used in a way that gave rise to false interpretation of the corporate actions, corporate policies, or investment decisions. For example, a story shared on social media falsely claimed that the Target Corporation caved to pressure from President Obama and LGBT groups and instituted a chain- wide policy inviting transgender employees and customers to use the bathroom that matched their gender identity. Misleading content was frequently seen in fake news concerning corporate political involvement, race relations, foreign investment and local resources, as well as corporate layoff decisions. As Wardle (2017) suggested, a typical technique used by fake news was framing, which delimits information by selecting some aspects of reality and making them more noticeable than others in the communicating text (Entman, 1993). Unsurprisingly, misleading content was the most frequently politicized type of fake news. One possible reason could be that in the current politically polarized society, framing contentious social issues with misleading content may make it easier to deceive people, for instance due to implicit or explicit biases regarding religious and racial issues. The second most commonly seen type of fake news was false connection, which involves false inference or association. For example, a dip in the Target Corporation’s stock price occurred around the same time as a boycott against the store’s transgender bathroom policy in April 2016. Stories published on conservative-leaning news websites such as Breitbart, Freedom Outpost, and MRCTV claimed that Target’s stock price plummeted due to the boycott. False connection stories were mostly related to products or services, concerning issues such as promotions and freebies, product quality and safety, market change and market share, and alleged bad service. Often, they contained elements of truth, or at least some of the ancillary

10 Public Relations Journal Vol. 13 Issue 4 (October 2020) © 2020 Institute for Public Relations details surrounding the claims might be accurate (according to the Snopes fact-checking rating system). The majority of the false connection stories seemed not to be deliberately created to cause harm, but rather to misunderstand the scope of businesses’ promotion programs, or the reasons behind a stock price change or price fluctuation. These stories almost always involved consumers and corporate customers. This might be because these stakeholders are relatively sensitive to changes in prices, or due to the geographically boundless features of digital media, which enable consumers to spread the word rapidly across multiple media platforms. More generally, false connection stories’ frequent inclusion of partially true elements could lend credibility to the story. This, along with ambiguous wording, might lead people to view the content of the false stories primarily through the lens of personal prejudice without more careful cognitive processing. The third largest category, fabricated content, is self-explanatory. The fabricated messages had nothing to do with facts—although some of them sounded authentic. For example, a product was falsely claimed to be endorsed by some celebrities. Fabricated stories were mostly about race relations and product conspiracies. When they were created on the topic of race relations, the stories were politicized and involved consumers and customers and employees in addition to certain racial and ethnic groups. When the fabricated stories were created on the topic of product conspiracies, they were not politicized and only involved consumers and customers. Taken together, these findings provide two insights into the current environment for the practice of public relations. The first has to do with one of the biggest challenges businesses face today, what editors of The Wall Street Journal have called “the polarization of everything” (The Editorial Board, 2017). The ideological polarization in the U.S. political and social systems— fueled by social media—has created a highly charged environment for businesses. As this study revealed, nearly half of the fake news stories were politicized—they contained issues with apparent or potential political implications such as corporate political involvement, race relations, corporate layoff decisions, and corporate response to minimum wage increases. Additionally, those politicized stories purposefully addressing a particular social group, such as Native Americans, African Americans, white supremacists, right-wing minimum wage opponents, anti-corporatist populists, animal rights activists, or conservative advocates, were more readily relayed among like-minded audiences on social media. Companies are increasingly liable to attack because of actions or policies of theirs that are associable with some controversial social or political issue, particularly veteran-related issues, minimum wage, endorsement of social movements, LGBT rights, layoffs, overseas investments, and racial conflicts. At times, the spread of fake news was prompted by President Donald Trump’s criticisms or inspired by his campaign strategies. For example, the president said he was “never eating another Oreo again” because the cookie maker’s parent company, Nabisco, was falsely claimed to decide to close their Chicago plant and move all production of Oreos to Mexico. This study also found that companies’ relationships with the natural environment have attracted close scrutiny. Fake news about a company’s environmental practices (usually negative) easily harms the company’s reputation, as they could be regarded as socially irresponsible and attacked not only by environmental organizations but also individuals. The second major insight into the contemporary public relations world is that employees were one of the most frequently mentioned or implicated stakeholders when a company was involved in fake news. Companies fell victim to fake news because of their decisions with regard to employee benefits and wellness, layoffs, minimum wages, and sub-groups of employees (e.g.,

LGBT people and Muslims). Very often, fake news stories involving employees were framed so that the issues were no longer confined to the company but instead associated with a broader social and political issue or a specific social group. For example, The Wendy's Company was alleged to have replaced human workers with self-service kiosks in order to reduce costs and cope with a federal minimum wage increase. The Target Corporation was falsely said to have used a sign to inform customers purchasing pork and alcohol to go to another checkout lane, as a gesture to accommodate Muslim cashiers. The Target Corporation also faced a separate fake news attack related to the company’s inclusive bathroom policy allowing transgender employees to use the bathroom that matched their gender identity. These findings suggest that companies should consider the social, ethical, and political implications of their employee-related decisions. Theoretical and Practical Implications This study’s major theoretical implication is that it provides one of the few empirical assessments of the issue of fake news in the business world. As companies have long been a target of disinformation and hoaxes, an empirical examination of different aspects and components of fake news content as well as the linkages between fake news content and sociopolitical contexts can fill important gaps in the existing research on fake news. The findings also indicate some important practical considerations for public relations professionals. As the results suggest, the most common types of fake news in the business context—misleading content, false connection, and fabricated content—typically presented partially or fully factual material in ways that created the wrong impressions or interpretations of the intentions behind corporate actions, policies, and investment decisions, as well as of the scope of promotional programs and even of product designs. Accordingly, companies should be mindful of the clarity and effectiveness of their communications regarding these areas. Companies should emphasize authenticity, which has been found to predict publics’ evaluation and perception of the genuineness, trustworthiness, credibility, and sincerity of the corporate communication or behavior (Beverland, 2006). Companies also need to realize that their delineation of the scope of promotional programs can easily be obfuscated by the connectedness and information diffusion of the Internet. Therefore, companies need to indicate more clearly the specific time frame and locations of their promotions. Furthermore, the findings suggested that corporations’ internal policies and practices (such as employee-related policies) were often influenced by the broader sociopolitical environment and in turn impacted the larger society and politics. Companies should thus adopt the systems perspective of issues management theory, proactively incorporating evaluations of external implications when making internal policies and decisions, before the crisis even begins. Limitations and Future Research This content analysis has several limitations that must be considered. First of all, rather than focusing on conceptualizing “fake news,” this study examined real-world fake news stories that were collected from a fact-checking website that has been referred to by the news media and other sites, including Facebook, CNN, MSNBC, Fortune, Forbes, and The New York Times. While the purpose of this study was to provide a preliminary examination of fake news about companies, a solid conceptual framework for examining fake news is still necessary for future research and theory building. Moreover, this study focused on the fake news content rather than the influence of the false content on the companies. Future work could assess how consumers would cognitively,

12 Public Relations Journal Vol. 13 Issue 4 (October 2020) © 2020 Institute for Public Relations affectively, or behaviorally respond to different types of association of brands and fake news, such as companies being the target of fake news, or corporate ads appearing adjacent to the questionable content. Finally, this study did not ground its examination of the fake news phenomenon in an existing theoretical framework. While the inductive approach of the study helped shed some light on a relatively new phenomenon, extending the current public relations and brand management knowledge into the study of fake news would illuminate potential impacts of fake news on the side of consumers and provide guidance on tackling the public’s brand misconceptions and on responding to false information to protect brand value. For example, it might be interesting to explore fake news and brands within the crisis management and issues management frameworks. In fact, fake news as a potential crisis for a company has already drawn attention from public relations practitioners, who have called for integrating fake news scenarios into corporations’ crisis communication plans (Agudelo, 2017; Dietrich, 2018; Gordon, 2018; Guillory, 2018; Liffreing, 2016). Further research taking this managerial perspective would likely yield insights that could inform public relations theory and practice.

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Table 1 Definition of Fake News Types (Wardle, 2017) Type Definitions False connection When false inference or association is made. Misleading content When information is misleadingly used to frame an issue or an individual to give the wrong ideas or impressions of the corporate actions, policies, investment decisions, etc. False context When genuine content is shared with false contextual information. Imposter content When genuine sources are impersonated by false, made-up sources. Manipulated When genuine information or imagery is manipulated to deceive, as with content a doctored photo. Fabricated content When content is 100% false, designed to deceive and do harm.

Table 2 Primary Industry Classification of the Companies Industries Frequency Companies Restaurants 8 Chick-fil-A, Burger King, McDonald’s, Starbucks, Wendy’s Hypermarkets and Supercenters 7 Walmart, Costco General Merchandise Stores 5 Target Packaged Foods and Meats 5 Cold Stone Creamery, Mars, Mondelez International, Nestlé Footwear 3 NIKE, Vans Apparel, Accessories, and Luxury Goods 2 Eddie Bauer, Luxottica Group Automobile Manufacturers 2 Ford Motor, General Motors Data Processing and Outsourced Services 2 EMVCo, Gravity Payments Department Stores 2 Hudson’s Bay, Macy’s Internet Software and Services 2 Ancestry.com, Pandora Media Leisure Products 2 Mattel, Ty Soft Drinks 2 Coca-Cola, Dr Pepper Airlines 1 United Airlines Application Software 1 Uber Automotive Retail 1 QuikTrip Broadcasting 1 Fox News Channel Business Services Sector 1 Confluence Food Retail 1 Whole Foods Home Improvement Retail 1 B&Q Housewares and Specialties 1 Pembient Information Technology Services 1 Etermax Internet and Direct Marketing Retail 1 Harry & David Metals and Mining 1 Rio Tinto Motorcycle Manufacturers 1 Harley-Davidson Movies and Entertainment 1 Warner Communications Oil and Gas Storage and Transportation 1 Dakota Access Specialty Stores 1 Santori Technology Hardware, Storage, and Peripherals 1 Apple Textile Manufacturing 1 TOM BIHN Wireless Telecommunication Services 1 EE Limited Unknown 1 Alpha ZXT TOTAL 61

Table 3 Thematic Issues in Fake News Stories Thematic Issues Frequency Percentage Examples of Fake News Stories Product 8 13.1 Symbols embossed on the exterior surfaces of Oreo conspiracies cookies link the product to the alleged conspiratorial activities of the Knights Templar and Freemasons. Alleged bad 7 11.5 Retailers are using “disappearing ink” on receipts to limit service or enforce a strict window on returns. Promotion and 6 9.8 You can get free Wendy’s Frostys all year long if you freebies purchase a $1 Frosty Key Tag. Race relations 6 9.8 DNA testing companies admitted to tampering with results in order to agitate racist customers. Corporate 5 8.2 The streaming music service Pandora endorsed the Black political Lives Matter movement while ignoring the deaths of involvement Dallas police officers. Product quality 3 4.9 A Harvard study proved that Apple purposely slows down and safety its older model iPhones to coincide with device releases and to boost sales of new models. Celebrity 2 3.3 Alpha ZXT was endorsed by Denzel Washington, Jamie endorsements Foxx, and Tiger Woods. Critique of CSR 2 3.3 Eddie Bauer clothing stores destroy and discard leftover products rather than giving them intact to charity. Employment and 2 3.3 In January 2018, Walmart announced a plan to close 250 hiring practices Sam’s Club warehouses, leaving 100,000 workers jobless. Foreign 2 3.3 Michigan is about to sell 100 million gallons of investment and groundwater to Nestlé for $200. local resources Lawsuit and 2 3.3 Sophia Stewart won a large judgment in a copyright legal infringement suit over authorship of the film The Matrix. Market change 2 3.3 Luxottica controls 80% of eyewear brands, several major and market share optometry chains, and the second-largest vision care insurer. Minimum wage 2 3.3 Wendy’s restaurants replaced workers with machines at thousands of locations because of a hike in the minimum wage. Price fluctuation 2 3.3 Uber increased its prices in parts of London around the and unwanted time of a terror attack in June 2017. fees Target of 2 3.3 Target’s stock price has plummeted due to a boycott over activism the store's transgender restroom policy. Anti-corporatism 1 1.6 Developers plan to build a super mall in the Grand Canyon. Business 1 1.6 Chick-fil-A restaurants have announced they will be operations reversing their longstanding policy and start opening on Sundays. Corporate 1 1.6 A biotech company has developed a 3D synthetic rhino environmental horn that will eventually undercut the market for poached practices horns. Historical 1 1.6 In accordance with a requirement of their original Royal corporate Charter, the Hudson’s Bay Company of Canada makes controversies annual payments of elk and beaver pelts to the Queen of England. Legislation and 1 1.6 The Fox News Channel has been banned in Canada regulation because they report false information.

Patriotism 1 1.6 Organizers of a barbecue event in Alabama forced participants to remove American flags from display. Religious 1 1.6 Walmart has discontinued the sale of all merchandise that is Bible-related or labeled as “made in America” to avoid offending people. Veteran-related 1 1.6 Macy’s refused to hire an applicant because she was a veteran who had served in Afghanistan. Total 61 Note. Each sample story may contain more than one issue, but we only recorded the most salient one. Therefore, the thematic issues were treated as mutually exclusive.

Table 4 Stakeholders of the Companies Involved in the Fake News Stories Stakeholders Frequency Percentage Customers or consumers 33 54.1 Nonprofit organizations (including activist groups) 14 23.0 Racial and ethnic groups 10 16.4 Employees 9 14.8 Foreign countries and foreign leaders 9 14.8 Governments and government officials 6 9.8 Slanted websites 5 8.2 Members of Congress and lawmakers 4 6.6 Donald Trump 3 4.9 Business leaders 2 3.3 Political parties 2 3.3 Protesters 2 3.3 Celebrities 2 3.3 Research institutions 1 1.6 Veterans 1 1.6 Note. Each sample story may involve more than one stakeholder. For each story, we recorded all the stakeholders involved.